Skill

Generate High-Converting Landing Pages

Generates complete Next.js/React landing pages from a product brief: TSX sections, Tailwind styling, SEO meta, and converting copy.

Works with reactnextjsgithub

81
Spark score
out of 100
Updated 5 days ago
Version 15.8.0

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Why it matters

Create complete, conversion-focused landing pages for your product. This asset generates Next.js/React components with optimized copy, SEO, and performance-first patterns.

Outcomes

What it gets done

01

Generate Next.js/React landing page components

02

Write conversion-focused copy using frameworks like PAS, AIDA, or BAB

03

Implement SEO best practices and structured data

04

Apply Tailwind CSS for various design styles

Install

Add it to your toolbox

Run in your project directory:

curl -fsSL https://spark.entire.vc/get/ag-landing-page-generator | bash

Overview

Landing Page Generator

A landing-page generation skill that produces complete Next.js/React sections (hero, features, pricing, FAQ, testimonials, CTA, footer) in Tailwind CSS with SEO metadata and conversion-focused copy. Use when generating a full marketing landing page from a product brief in Next.js or React; not for building isolated UI fragments without landing-page context.

What it does

Generates complete, high-converting Next.js/React landing pages from a product description: TSX components, Tailwind styling, SEO meta, and structured copy - not placeholder lorem ipsum. Covers five hero variants (centered, split, gradient, video-bg, minimal), feature sections (grid, alternating, cards with icons), pricing tables (2-4 tiers with feature lists and toggle), an FAQ accordion with FAQPage JSON-LD schema markup, testimonials (grid, carousel, single-quote), CTA sections (banner, full-page, inline), and footers (simple, mega, minimal), across four named design styles - Dark SaaS, Clean Minimal, Bold Startup, Enterprise - each with its own Tailwind class set for background, accent, cards, and CTA buttons. It follows a seven-step generation workflow: gather inputs (product name, tagline, audience, pain point, benefit, pricing, design style, copy framework), optionally analyze brand voice via brand_voice_analyzer.py to infer style and framework, select the design style, write all copy using the chosen framework, generate sections in a fixed order (Hero, Features, Pricing, FAQ, Testimonials, CTA, Footer), validate against an eleven-item SEO checklist, then output copy-paste-ready TSX. Copy is written using one of three frameworks - PAS (Problem-Agitate-Solution), AIDA (Attention-Interest-Desire-Action), or BAB (Before-After-Bridge) - each mapped by the skill to a specific design style based on the analyzed brand voice, for example a formal, professional voice maps to Enterprise style with AIDA copy.

When to use - and when NOT to

Use when generating a marketing landing page in Next.js or React that needs conversion-focused structure, section variants, Tailwind styling, and SEO-aware copy - specifically when the goal is complete landing-page output from a product description rather than isolated UI fragments. The skill's own related-skills list routes design-token generation to a separate UI Design System skill and competitive-positioning research to a Competitive Teardown skill, expecting those to run before this one rather than duplicating that work here.

Inputs and outputs

Input is a structured product brief - name, tagline, target audience, pain point, key benefit, pricing tiers, design style, and copy framework - plus optionally existing brand content for voice analysis. Output is complete TSX components with Tailwind classes, SEO meta tags, and structured data (FAQPage, Product, or Organization JSON-LD), targeting Core Web Vitals of LCP under 1s, CLS under 0.1, and FID/INP under 100ms through techniques like hero-image preloading, explicit image dimensions, deferred non-critical JS, and static or ISR rendering.

Integrations

Built for Next.js/React with Tailwind CSS and shadcn's <Accordion> component; integrates with marketing-skill/content-production/scripts/brand_voice_analyzer.py for voice-informed style selection, and is designed to run after a product-team/ui-design-system/ design-token pass and a product-team/competitive-teardown/ positioning pass.

Who it's for

Product and growth engineers who need a complete, SEO-optimized, performance-budgeted landing page generated from a product brief rather than assembling one section at a time.

FAQ

Common questions

Discussion

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